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Machine Learning Software Engineer Intern Jobs in Burlingame, CA

Ema

Software Engineer, Machine Learning

San Francisco, CA · On-site

$160K - $220K/yr

Who You Are We're looking for innovative and passionate Machine Learning Engineers to join our team ... Good understanding of software development principles, data structures, and algorithms. * Excellent ...

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All JobsMachine Learning Software Engineer Intern JobsMachine Learning Software Engineer Intern Jobs in Burlingame, CA

Machine Learning Software Engineer Intern information

See Burlingame, CA salary details

$15

$28

$43

How much do machine learning software engineer intern jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for machine learning software engineer intern in Burlingame, CA is $28.70, according to ZipRecruiter salary data. Most workers in this role earn between $23.37 and $32.55 per hour, depending on experience, location, and employer.

What does a machine learning software engineer intern do?

A Machine Learning Software Engineer Intern assists in the development, testing, and deployment of machine learning models and algorithms. Their responsibilities typically include data preprocessing, model training, evaluation, and collaborating with senior engineers to integrate machine learning solutions into software products. Interns may also contribute to research, documentation, and code optimization, gaining hands-on experience with real-world machine learning projects. This role provides a valuable opportunity to apply academic knowledge in a professional setting and learn from experienced engineers.

What are the key skills and qualifications needed to thrive as a machine learning software engineer intern?

To thrive as a Machine Learning Software Engineer Intern, you need a solid understanding of programming (especially Python), machine learning algorithms, and data structures, ideally supported by coursework or relevant projects. Familiarity with frameworks such as TensorFlow or PyTorch, experience using version control systems like Git, and knowledge of cloud platforms are highly valuable. Critical thinking, eagerness to learn, and effective communication help interns collaborate with teams and adapt to new challenges. These skills and qualities are crucial for developing robust ML solutions, integrating with production systems, and contributing meaningfully to real-world projects.
What cities near Burlingame, CA are hiring for Machine Learning Software Engineer Intern jobs? Cities near Burlingame, CA with the most Machine Learning Software Engineer Intern job openings:
Machine Learning Software Engineer Intern jobs near you

Senior Machine Learning Engineer -- VETi Platform

Kodiak Sciences Inc.

Palo Alto, CA • On-site

$144K - $198K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Kodiak Sciences (Nasdaq: KOD) is advancing vision science by integrating retinal biology, optics, artificial intelligence, medical imaging, and next-generation wearable technologies.
Our VETi™ — Visual Engagement Technology and Imager — platform is an AI-enabled wearable system combining advanced LiDAR, Optical Coherence Tomography (OCT), embedded computing, machine learning, and AR/VR technologies. VETi is being developed for applications in retina care, digital health, identity security, cognitive science, and broader AI-enabled vision technologies.
 
We are looking for a Senior Machine Learning Engineer to build the AI foundation for Kodiak’s VETi platform, from model research and training to deployment on embedded medical imaging hardware. This role is well suited for an engineer with strong machine learning and software fundamentals who enjoys complex computer vision problems and is excited to ship AI that runs on real wearable devices. 

Responsibilities

  • Lead the design, training, and deployment of machine learning models for wearable imaging and sensing systems — from research prototypes through production.
  • Develop computer vision models for image processing and analysis across multiple imaging modalities and sensors.
  • Analyze medical imaging data with deep learning models to support diagnostics and clinical decision-making.
  • Build training pipelines, data labeling workflows, and evaluation frameworks that scale across imaging datasets.
  • Integrate and optimize AI inference into the VETi platform’s real-time imaging and device-control stack, deploying to NPUs, GPUs, and embedded accelerators within latency, power, and memory budgets.
  • Debug model accuracy and performance across training, evaluation, and on-device environments.
  • Collaborate with electrical, optics, clinical, software, and systems engineering teams.
Education / Required Qualifications
  • B.S., M.S., or Ph.D. in AI, Computer Science, Electrical Engineering, Applied Mathematics, Physics, or a related technical discipline, or equivalent practical experience.
  • 5+ years of professional machine learning experience developing and deploying production models.
  • Strong programming experience in Python and C++, with at least one major ML framework (PyTorch, TensorFlow, or JAX) and solid software engineering practices.
  • Strong deep learning experience, particularly in computer vision (CNNs, transformers, segmentation, detection, classification).
  • Experience deploying models to edge devices, including model optimization (quantization, pruning, distillation) and inference runtimes (ONNX, TensorRT, or similar).
  • Ability to collaborate across machine learning, software, hardware, scientific, and engineering teams.

Additional Experience That Would Be Valuable

  • Experience with medical imaging data (OCT, fundus, retinal scans, MRI, CT, or similar).
  • Experience working with 3D or volumetric imaging data (e.g., OCT B-scans, volumetric MRI/CT).
  • Experience building AI agents for user interaction or human-in-the-loop systems.
  • Experience with self-supervised learning, transfer learning, or other data-efficient methods for limited labeled data.
  • Familiarity with regulated medical-device AI development (FDA SaMD, IEC 62304, ISO 13485), or willingness to learn.
Why Join Kodiak
This role is an opportunity to build AI for real-world physical systems—optics, sensors, and embedded computing—running on actual devices, not just in the cloud. You will work at the intersection of software, hardware, medical imaging, optics, AR/VR, LiDAR, OCT, and AI. The platform is novel, the technical challenges are significant, and the work has the potential to shape a new class of wearable vision technologies.